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Julie Pai and Majed Al-Ghandour

In this course, we will cover the basics of visualization and how it fits into the Data Science workflow. We will focus on the main concepts behind the purpose of visualization and the design principles for creating effective, easy-to-communicate results. You will also set up your Tableau environment, practice data loading, and perform univariate descriptive analysis of the S&P 500 stock sectors.

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What's inside

Syllabus

Visualization Fundamentals
Visualization is a crucial skill for data analysts across all disciplines. Viewing data graphically often provides greater intuition than by using statistics or mathematics alone. In this module, we’ll explore the fundamentals of visualization and discuss how visualizations can achieve better insight into data as well as effectively communicate results and conclusions.
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Design Principles for Effective Visualizations
To create effective visuals, analysts must understand and be able to explain why specific graphical elements must be included, eliminated, or modified. In this module, we’ll investigate why certain questions are best answered by specific visual cue patterns, discuss which psychological perception theories should be considered during the construction of data visualizations, and cover the universal framework for representing visual data, the grammar of graphics.
Univariate Visualization Methods
Univariate visualization methods apply the grammar of graphics to the representation of a dataset’s fundamental properties and structures in terms of single variable mappings to visual encodings. In this module, we’ll explore specifics for how to view the data and what to visualize and discuss ​​what mapping of data is best suited for highlighting and extracting insights from the data.
Standard Univariate Visualizations
Instead of reinventing the wheel with every visualization, analysts use several common chart types so there is no ambiguity about the decoding and interpretation of the data. In this module, we'll explore some standard tools and techniques that are used to prepare a fully crafted set of visualizations for the purpose of storytelling. Before completing this module, you will use Tableau to conduct a univariate analysis to sample data, compare dimensions vs. measures, and practice linking visualizations.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops foundational skills that are highly relevant to roles in data science and general business analysis
Teaches visual data storytelling that is used in all industries that collect and analyze data
Instructors have extensive experience in using visualization science to solve real-world problems
Primarily uses Tableau software, which is a top choice for data visualization in industry and academia

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Visualization Best Practices with these activities:
Connect with Tableau Experts
Provides access to experienced Tableau professionals who can offer guidance, support, and insights, accelerating your learning journey.
Show steps
  • Join online Tableau communities or forums
  • Attend local Tableau user group meetings
  • Reach out to Tableau experts via social media or email
Read 'The Visual Display of Quantitative Information' by Edward Tufte
Exposes you to fundamental principles of data visualization from a renowned expert, enhancing your understanding of effective visual communication.
View Beautiful Evidence on Amazon
Show steps
  • Read the book thoroughly
  • Analyze the examples and case studies provided
  • Apply the principles to your own visualization projects
Review Basic Statistical Concepts
Ensures you have a solid foundation in statistical concepts, enabling you to better comprehend the data you're visualizing.
Browse courses on Basic Statistics
Show steps
  • Revisit concepts of central tendency (mean, median, mode)
  • Review measures of dispersion (range, standard deviation, variance)
  • Recall basic probability distributions (normal, binomial, Poisson)
One other activity
Expand to see all activities and additional details
Show all four activities
Design a Tableau Visualization for a Real-World Problem
Empowers you to apply your visualization skills to solve real-world problems, showcasing your ability to communicate insights effectively.
Show steps
  • Identify a real-world problem or dataset
  • Clean and prepare the data
  • Design and create a Tableau visualization
  • Write a brief report explaining your findings

Career center

Learners who complete Data Visualization Best Practices will develop knowledge and skills that may be useful to these careers:
Data Visualization Analyst
Data Visualization Analysts create visual representations of data to help businesses understand and communicate complex information. This course can help build a foundation for a career as a Data Visualization Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods.
Business Intelligence Analyst
Business Intelligence Analysts use data to identify trends and patterns that can help businesses make better decisions. This course can help build a foundation for a career as a Business Intelligence Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Data Analyst
Data Analysts use data to solve business problems and make informed decisions. This course can help build a foundation for a career as a Data Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to effectively communicate data-driven insights to stakeholders.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. This course can help build a foundation for a career as a Marketing Manager by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Sales Manager
Sales Managers are responsible for leading and motivating sales teams. This course can help build a foundation for a career as a Sales Manager by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Data Scientist
Data Scientists use data to solve complex problems and develop new products and services. This course can help build a foundation for a career as a Data Scientist by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Product Manager
Product Managers are responsible for the development and launch of new products and services. This course can help build a foundation for a career as a Product Manager by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Market Research Analyst
Market Research Analysts use data to understand consumer behavior and trends. This course can help build a foundation for a career as a Market Research Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
User Experience (UX) Researcher
User Experience (UX) Researchers study how users interact with products and services. This course can help build a foundation for a career as a User Experience (UX) Researcher by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Quantitative Analyst
Quantitative Analysts use data to develop and implement trading strategies. This course can help build a foundation for a career as a Quantitative Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Statistician
Statisticians use data to collect, analyze, and interpret data. This course can help build a foundation for a career as a Statistician by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Financial Analyst
Financial Analysts use data to evaluate investments and make recommendations to clients. This course can help build a foundation for a career as a Financial Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Risk Analyst
Risk Analysts use data to identify and assess risks to businesses. This course can help build a foundation for a career as a Risk Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency and effectiveness of business operations. This course can help build a foundation for a career as an Operations Research Analyst by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods. This course can help you learn how to use data visualization to communicate insights to stakeholders.
Data Engineer
Data Engineers design, build, and maintain data pipelines. This course may be useful for those interested in a career as a Data Engineer by providing a comprehensive overview of the fundamentals of visualization, design principles, and univariate visualization methods.

Reading list

We've selected 13 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Visualization Best Practices.
A classic in the field, providing foundational principles and guidelines for effective data visualization, enhancing the course's theoretical underpinnings.
Provides a comprehensive treatment of information visualization, covering both theoretical foundations and practical techniques, expanding on the course's core concepts.
Focuses on the art of communicating data effectively through compelling visuals, complementing the course's emphasis on presenting insights clearly.
A seminal work in data visualization, offering advanced insights and techniques for creating effective and informative visuals, further expanding on the course's theoretical foundation.
Examines common pitfalls and biases in data visualization, providing valuable insights into the responsible use of visuals and enhancing the course's emphasis on ethical practices.
Explores the cognitive processes involved in visual perception and how they relate to data visualization, offering insights into the human factors behind effective visuals.
Focuses on the ethics and responsible use of data visualization, complementing the course's emphasis on communicating insights clearly and accurately.
Focuses on using the ggplot2 library in R for data visualization, offering practical insights and examples that complement the course's hands-on component.
Provides a foundation in reading and interpreting charts and graphs, serving as a valuable resource for the course's emphasis on data exploration and analysis.

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